Neste trabalho, as restrições de estabilidade transitória são incorporadas ao problema de Fluxo de Potência Ótimo (FPO) por meio da aproximação de equações diferenciais do problema de estabilidade por um conjunto de equações algébricas provenientes de procedimentos de integração numérica. Uma contribuição original desta dissertação é a proposição de um procedimento de otimização multi-passos que minimiza problemas de convergência e acelera o processo computacional. O procedimento de otimização proposto foi testado com sucesso num sistema pequeno de 3 geradores, tendo as potências geradas como variáveis de controle. / In this work, transient stability constraints are incorporated into the Optimal Power Flow (OPF) problem by approximating differential equations constraints by a set of equivalent algebraic equations originated from numerical integration procedures. A contribution of this dissertation is the proposal of a multi-step optimization procedure, which minimizes convergence problems and speeds up computation. The proposed optimization procedure was successfully tested on a small 3-machine power system, having the generated powers as control variables.

Optimal transmission switching (OTS) enables us to remove selected transmission lines from service as a cost reduction method. A mixed integer programming (MIP) model has been proposed to solve the OTS problem based on the direct current optimal power flow (DCOPF) approximation. Previous studies indicated computational issues regarding the OTS problem and the need for a more accurate model. In order to resolve computational issues, especially in large real systems, the MIP model has been followed by some heuristics to find good, near optimal, solutions in a reasonable time. The line removal recommendations based on DCOPF approximations may result in poor choices to remove from service. We assess the quality of line removal recommendations that rely on DCOPF-based heuristics, by estimating actual cost reduction with the exact alternating current optimal power flow (ACOPF) model, using the IEEE 118-bus test system. We also define an ACOPF-based line-ranking procedure and compare the quality of its recommendations to those of a previously published DCOPF-based procedure. For the 118-bus system, the DCOPF-based line ranking produces poor quality results, especially when demand and congestion are very high, while the ACOPF-based heuristic produces very good quality recommendations for line removals, at the expense of much longer computation times. There is a need for approximations to the ACOPF that are accurate enough to produce good results for OTS heuristics, but fast enough for practical use for OTS decisions.

In recent years, with the energy shortage, the use of renewable energy is inevitable. With CO2 the most important greenhouse gas causing global warming as well as the increase of population, renewable energy is one way to save energy and reduce carbon emissions. The traditional capacity investment for serving the load in distribution systems usually considered the addition of new substations or expansion of the existing substation and associated new feeder requirement. Nowadays, there are a lots of distributed generations (DG¡¦s) to be chosen. Factors of the choice taken into account will include lower pollution, higher efficiency, higher return rate for construction of distributed power generation systems. This thesis assumes that the distributed generation can be invested for long-term power plant planning. The planning of DG would be investigated from the perspectives of the independent investors. The modified Particle Swarm Optimization is proposed to determine the optimal sizing and sit of DG¡¦s addition in distribution systems with the constrains of CO2 limitation and addition of distributed generation to maximize profits. This thesis deals with discrete programming problem of optimal power flow, which includes continuous and discrete types of variables. The continuous variables are the generating unit real power output and the bus voltage magnitudes, the discrete variables are the shunt capacitor banks and sit problems. The Miaoli-Houlong system of Taiwan power will be used in this thesis for the verification of the feasibility of the proposed method.

With the deregulation of power industry and the market competition, low cost, reliable power supply, and secured system operations are major concerns of the advanced deregulation markets. Power system protection is important for service reliability and quality assurance. To reduce the outage duration and promptly restore power services, fault section estimate has to be done effectively and accurately with fault alarms. First, an operational strategy for secondary power system restoration using Modified Grey Relational Analysis (MGRA) is proposed. The Restoration Scheme (RS) can be divided into three steps involving fault section determination, recovering process, and voltage correction process. Three GRAs are incorporated to design the overall restoration scheme. The first GRA uses network switching status to identify the fault. The second GRA combines switching states and load levels for network recovery. The third GRA uses capacitor bank control to support bus voltages. For security operation of restoration scheme, an Equivalent Current Injection (ECI) based hybrid current-power Optimal Power Flow (OPF) model with Predictor-Corrector Interior Point Algorithm (PCIPA) is used to verify the proposed scheme by off-line analysis to confirm a secure overall network operation including load-power balance, power generation limits, voltage limits, and power flow limits. The proposed method can further decompose into two sub-problems. Computer simulations were conducted with an IEEE 30-bus power system to show the effectiveness of the proposed restoration scheme and the PCIPA technique is very accurate, robust, and efficient for the modified OPF solution.

<p>This thesis is based on studies of the deregulated electricity markets located in the United States of America. The problem statement of the thesis evolved continuously throughout our initial period of research. Focus was finally put on monitoring and detection of potential market power caused by congestion in the transmission network. The existence of market power is a serious concern in today’s electric energy markets. A system that monitors the trading is needed and much research and many proposals on how to deal with this problem have been introduced over the years. We focus on some of these approaches and develop an approach of our own, which we call “Monopolistic Energy Calculation”. We adopt the idea to identify participants with the ability to raise prices without losing market share. An ability that should not be present on a competitive market. We take this idea further by identifying participants with the ability to make considerable price raises without losing all market shares. We propose a way to calculate the remaining market shares (Monopolistic Energy Levels) after a large price raise. These calculated levels of energy, that are only deliverable by a certain participant or by a certain group of participants, are caused by the active congestions in the network.</p><p>The approach detects the amounts of these energy levels and the location in the network at which they are present. This is a prospective method if used with a prediction of the following day’s demand, which is regularly available with high accuracy. The method can also be used for monitoring purposes to identify critical situations in real-time. The method is implemented and two sets of simulations are done in which we explain and evaluate the approach. The results are promising and the correlation between “Monopolistic Energy” and market power is confirmed.</p> / <p>Detta examensarbete är baserat på studier av de deregulerade electricitsmarknaderna i USA. Problemformuleringen var i början av detta arbete inte definitiv, utan utvecklades under en längre inledande fas av forskningsarbete. Slutligen kunde vi faställa att detektion av potentiell marknadskraft på elektricitetsmarknaden, orsakat av överbelastningar i transmissionnätverket, var av särskilt intresse. Ett system som övervakar handeln och förekomster av orättvisor orsakat av detta är nödvändigt. Det har de senaste åren gjorts mycket forskning inom detta område. Baserat på denna forskning utvecklades sedan ett eget förslag, som vi kallar ”Monopolistic Energy Calculations”. Vissa tidigare förslag på hur problemet kan angripas blev av särskilt intresse. En idé från dessa var att identifiera marknadsaktörer med förmågan att höja priser utan att förlora marknadsandelar, en icke önskvärd egenskap hos aktörer då en konkurrenskraftig marknad är eftertraktad.</p><p>Vi tar denna idé ett steg längre genom att identifiera marknadsaktörer med förmågan att höja priser signifikant utan att förlora alla marknadsandelar. Vi föreslår ett sätt att beräkna dessa energinivåer som endast är möjliga att levereras av en eller ett fåtal särskilda aktörer, som direkt följd av de aktiva stockningarna i nätverket, under antagandet av en inelastisk efterfrågan. Vi föreslår ett sätt att beräkna de återstående marknadsandelarna (Monopolistic Energy Levels) efter en stor prishöjning. Vår metod beräknar mängden av denna energi och var i nätverket dessa mängder förekommer. Denna metod kan sia om framtida problem om en estimering av morgondagens efterfråga används. Sådana estimeringar görs idag</p><p>regelbundet med hög träffsäkerhet. Metoden kan även användas i realtid för upptäckt av kritiska marknadssituationer. Simuleringar av detta görs som förklarar vår lösning och utvärderar den. Resultaten är lovande och korrelationen mellan ”Monopolistisk Energi” och marknadskraft är bekräftade.</p>

The contributions of the research are (a) an infrastructure of data acquisition systems that provides the necessary information for an automated EMS system enabling autonomous distributed state estimation, model validation, simplified protection, and seamless integration of other EMS applications, (b) an object-oriented, interoperable, and unified component model that can be seamlessly integrated with a variety of applications of the EMS, (c) a distributed dynamic state estimator (DDSE) based on the proposed data acquisition system and the object-oriented, interoperable, and unified component model, (d) a physically-based synchronous machine model, which is expressed in terms of the actual self and mutual inductances of the synchronous machine windings as a function of rotor position, for the purpose of synchronous machine parameters identification, and (e) a robust and highly efficient algorithm for the optimal power flow (OPF) problem, one of the most important applications of the EMS, based on the validated states and models of the power system provided by the proposed DDSE.

This thesis is based on studies of the deregulated electricity markets located in the United States of America. The problem statement of the thesis evolved continuously throughout our initial period of research. Focus was finally put on monitoring and detection of potential market power caused by congestion in the transmission network. The existence of market power is a serious concern in today’s electric energy markets. A system that monitors the trading is needed and much research and many proposals on how to deal with this problem have been introduced over the years. We focus on some of these approaches and develop an approach of our own, which we call “Monopolistic Energy Calculation”. We adopt the idea to identify participants with the ability to raise prices without losing market share. An ability that should not be present on a competitive market. We take this idea further by identifying participants with the ability to make considerable price raises without losing all market shares. We propose a way to calculate the remaining market shares (Monopolistic Energy Levels) after a large price raise. These calculated levels of energy, that are only deliverable by a certain participant or by a certain group of participants, are caused by the active congestions in the network. The approach detects the amounts of these energy levels and the location in the network at which they are present. This is a prospective method if used with a prediction of the following day’s demand, which is regularly available with high accuracy. The method can also be used for monitoring purposes to identify critical situations in real-time. The method is implemented and two sets of simulations are done in which we explain and evaluate the approach. The results are promising and the correlation between “Monopolistic Energy” and market power is confirmed. / Detta examensarbete är baserat på studier av de deregulerade electricitsmarknaderna i USA. Problemformuleringen var i början av detta arbete inte definitiv, utan utvecklades under en längre inledande fas av forskningsarbete. Slutligen kunde vi faställa att detektion av potentiell marknadskraft på elektricitetsmarknaden, orsakat av överbelastningar i transmissionnätverket, var av särskilt intresse. Ett system som övervakar handeln och förekomster av orättvisor orsakat av detta är nödvändigt. Det har de senaste åren gjorts mycket forskning inom detta område. Baserat på denna forskning utvecklades sedan ett eget förslag, som vi kallar ”Monopolistic Energy Calculations”. Vissa tidigare förslag på hur problemet kan angripas blev av särskilt intresse. En idé från dessa var att identifiera marknadsaktörer med förmågan att höja priser utan att förlora marknadsandelar, en icke önskvärd egenskap hos aktörer då en konkurrenskraftig marknad är eftertraktad. Vi tar denna idé ett steg längre genom att identifiera marknadsaktörer med förmågan att höja priser signifikant utan att förlora alla marknadsandelar. Vi föreslår ett sätt att beräkna dessa energinivåer som endast är möjliga att levereras av en eller ett fåtal särskilda aktörer, som direkt följd av de aktiva stockningarna i nätverket, under antagandet av en inelastisk efterfrågan. Vi föreslår ett sätt att beräkna de återstående marknadsandelarna (Monopolistic Energy Levels) efter en stor prishöjning. Vår metod beräknar mängden av denna energi och var i nätverket dessa mängder förekommer. Denna metod kan sia om framtida problem om en estimering av morgondagens efterfråga används. Sådana estimeringar görs idag regelbundet med hög träffsäkerhet. Metoden kan även användas i realtid för upptäckt av kritiska marknadssituationer. Simuleringar av detta görs som förklarar vår lösning och utvärderar den. Resultaten är lovande och korrelationen mellan ”Monopolistisk Energi” och marknadskraft är bekräftade.

The deployment of Renewable Energy (RE)-based generation has experienced a sustained global growth in the recent decades, driven by many countries' interest in reducing greenhouse gas emissions and dependence on fossil fuel for electricity generation. This trend is also observed in remote off-grid systems (isolated microgrids), where local communities, in an attempt to reduce fossil fuel dependency and associated economic and environmental costs, and to increase availability of electricity, are favouring the installation of RE-based generation. This practice has posed several challenges to the operation of such systems, due to the intermittent and hard-to-predict nature of RE sources. In particular, this thesis addresses the problem of reliable and economic dispatch of isolated microgrids, also known as the energy management problem, considering the uncertain nature of those RE sources, as well as loads. Isolated microgrids feature characteristics similar to those of distribution systems, in terms of unbalanced power flows, significant voltage drops and high power losses. For this reason, detailed three-phase mathematical models of the microgrid system and components are presented here, in order to account for the impact of unbalanced system conditions on the optimal operation of the microgrid. Also, simplified three-phase models of Distributed Energy Resources (DERs) are developed to reduce the level of complexity in small units that have limited impact on the optimal operation of the system, thus reducing the number of equations and variables of the problem. The proposed mathematical models are then used to formulate a novel energy management problem for isolated microgrids, as a deterministic, multi-period, Mixed-Integer Nonlinear Programming (MINLP) problem. The multi-period formulation allows for a proper management of energy storage resources and multi-period constraints associated with the commitment decisions of DERs. In order to obtain solutions of the energy management problem in reasonable computational times for real-time, realistic applications, and to address the uncertainty issues, the proposed MINLP formulation is decomposed into a Mixed-Integer Linear Programming (MILP) problem, and a Nonlinear programming (NLP) problem, in the context of a Model Predictive Control (MPC) approach. The MILP formulation determines the unit commitment decisions of DERs using a simplified model of the network, whereas the NLP formulation calculates the detailed three-phase dispatch of the units, knowing the commitment status. A feedback signal is generated by the NLP if additional units are required to correct reactive power problems in the microgrid, triggering a new calculation MINLP problem. The proposed decomposition and calculation routines are used to design a new deterministic Energy Management System (EMS) based on the MPC approach to handle uncertainties; hence, the proposed deterministic EMS is able to handle multi-period constraints, and account for the impact of future system conditions in the current operation of the microgrid. In the proposed methodology, uncertainty associated with the load and RE-based generation is indirectly considered in the EMS by continuously updating the optimal dispatch solution (with a given time-step), based on the most updated information available from suitable forecasting systems. For a more direct modelling of uncertainty in the problem formulation, the MILP part of the energy management problem is re-formulated as a two-stage Stochastic Programming (SP) problem. The proposed novel SP formulation considers that uncertainty can be properly modelled using a finite set of scenarios, which are generated using both a statistical ensembles scenario generation technique and historical data. Using the proposed SP formulation of the MILP problem, the deterministic EMS design is adjusted to produce a novel stochastic EMS. The proposed EMS design is tested in a large, realistic, medium-voltage isolated microgrid test system. For the deterministic case, the results demonstrate the important connection between the microgrid's imbalance, reactive power requirements and optimal dispatch, justifying the need for detailed three-phase models for EMS applications in isolated microgrids. For the stochastic studies, the results show the advantages of using a stochastic MILP formulation to account for uncertainties associated with RE sources, and optimally accommodate system reserves. The computational times in all simulated cases show the feasibility of applying the proposed techniques to real-time, autonomous dispatch of isolated microgrids with variable RE sources.

Power flow (PF) control can increase the utilization of the transmission system and connect lower cost generation with load. While PF controllers have demonstrated the ability to realize dynamic PF control for more than 25 years, PF control has been sparsely implemented. This research re-examines PF control in light of the recent development of fractionally-rated PF controllers and the incremental power flow (IPF) control concept. IPF control is the transfer of an incremental quantity of power from a specified source bus to specified destination bus along a specified path without influencing power flows on circuits outside of the path. The objectives of the research are to develop power system operation and planning methods compatible with IPF control, test the technical viability of IPF control, develop transmission planning frameworks leveraging PF and IPF control, develop power system operation and planning tools compatible with PF control, and quantify the impacts of PF and IPF control on multi-decade transmission planning. The results suggest that planning and operation of the power system are feasible with PF controllers and may lead to cost savings. The proposed planning frameworks may incent transmission investment and be compatible with the existing transmission planning process. If the results of the planning tool demonstration scale to the national level, the annual savings in electricity expenditures would be $13 billion per year (2010$). The proposed incremental packetized energy concept may facilitate a reduction in the environmental impact of energy consumption and lead to additional cost savings.

Optimal transmission switching (OTS) enables us to remove selected transmission lines from service as a cost reduction method. A mixed integer programming (MIP) model has been proposed to solve the OTS problem based on the direct current optimal power flow (DCOPF) approximation. Previous studies indicated computational issues regarding the OTS problem and the need for a more accurate model. In order to resolve computational issues, especially in large real systems, the MIP model has been followed by some heuristics to find good, near optimal, solutions in a reasonable time. The line removal recommendations based on DCOPF approximations may result in poor choices to remove from service. We assess the quality of line removal recommendations that rely on DCOPF-based heuristics, by estimating actual cost reduction with the exact alternating current optimal power flow (ACOPF) model, using the IEEE 118-bus test system. We also define an ACOPF-based line-ranking procedure and compare the quality of its recommendations to those of a previously published DCOPF-based procedure. For the 118-bus system, the DCOPF-based line ranking produces poor quality results, especially when demand and congestion are very high, while the ACOPF-based heuristic produces very good quality recommendations for line removals, at the expense of much longer computation times. There is a need for approximations to the ACOPF that are accurate enough to produce good results for OTS heuristics, but fast enough for practical use for OTS decisions.